Based on the Retinex method and the SIFT feature analysis, this paper presents a novel algorithm for hand vein recognition. First of all, the principle of the near-infrared hand vein image acquisition is introduced. S...
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At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is us...
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At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is used to express binary form, which has a clear ascension whether in space or in time than the traditional discernibility matrix efficiency. On the basis of granularity-based attribute reduction, a method is proposed to preprocess the dataset by using binary discernibility matrix. Firstly, find the core attribute and a minimal reduction. Then use the granularity thought to calculate each particle of the importance of attributes. Most important is joined to the reduction set, thereby achieving the attributes reduction. The example analysis shows that the method can improve the performance of the traditional attribute reduction algorithms effectively. It is a feasible approach to reduce attributes.
Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering...
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Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering membership, which preprocesses the training datasets and extracts all possible support vectors for SVM training according to the memberships. Considering the training datasets may be linear or nonlinear, this paper severally uses FCM and KFCM to extract support vectors. Experiment results show that the method proposed in this paper can improve the training speed greatly in the condition of maintaining the classification accuracy.
Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set tha...
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Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set that is well-defined and pre-structured to a number of local models offline. In other words, given two image sets, as long as each of them is aligned to the reference set, they are mutually aligned and well structured. Therefore, the similarity between them can be computed by comparing only the corresponded local models rather than considering all the pairs. To align an image set with the reference set, we further formulate the problem as a quadratic programming. It integrates three constrains to guarantee robust alignment, including appearance matching cost term exploiting principal angles, geometric structure consistency using affine invariant reconstruction weights, smoothness constraint preserving local neighborhood relationship. Extensive experimental evaluations are performed on three databases: Honda, MoBo and YouTube. Compared with competing methods, our approach can consistently achieve better results.
Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising ...
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Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising improvement approach to cut down the testing cost. This paper introduces a technique that automatically generate real-time conformance test cases from timed automata specifications. First, both reactive system and its environment is modeled by restricted automata with the notion of deterministic, input enabled and output urgent. Then demonstration is given to show how to efficiently generate real-time test cases with optimal execution time from diagnostic trace. Finally, we formally specify user's single purpose or coverage criteria to convert the test case generation problem into a reachability problem. This approach is implemented using model checkers as test case generation tools and experiment results on three different coverage criteria specifications show feasibility and effectiveness of our technique.
The contradiction exists between high QoS requirements and the constrained resources in wireless multimedia sensor networks (WMSNs). To support multimedia applications, a novel routing scheme, ant-based clustered mult...
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Clear image stitching becomes mature now, but how to stitch blurred images with clear ones is still tough, mainly because of the ill-posed image deblurring. Existing deblurring methods assume spatial-invarint blur ker...
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Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy se...
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Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy set model based on fuzzy relations to vague sets. We mainly focus on the lower and upper approxima- tion operators of vague sets based on vague relations, and investigate the basic properties of approximation opera- tors on vague sets. Specially, we give some essential characterizations of the lower and upper approximation operators generated by reflexive, symmetric, and transi- tive vague relations. Finally, we structure a parameterized roughness measure of vague sets and similarity measure methods between two rough vague sets, and obtain some properties of the roughness measure and similarity measures. We also give some valuable counterexamples and point out some false properties of the roughness measure in the paper of Wang et al.
This paper present a geometric method to reconstruct human motion pose from 2D point correspondences obtained from uncalibrated monocular images. The proposed algorithm can handle images with very strong perspective e...
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An efficient SAR image fusion algorithm for multi - polarimetric images based on Directionlets transform is proposed. Directionlets transform is a new lattice-based multiscale analysis anisotropic multi-directional wa...
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